Model comparison
GPT-5.1 vs Muse Spark 1.3
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 49.0 on the Noometry Index.
Last verified . 28 shared benchmarks.
MetaSummary
- They share 28 benchmarks with published results for both. GPT-5.1 scores higher in 4 categories and Muse Spark 1.3 in 6 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where Muse Spark 1.3 leads 73.1 to 52.2.
- The biggest single-benchmark swing is CritPt: 4.9% for GPT-5.1 and 26% for Muse Spark 1.3.
- Muse Spark 1.3 is cheaper at $1.25 / $4.25 per million input/output tokens, against $1.25 / $10 for GPT-5.1.
- Muse Spark 1.3 accepts more context: 1.05M tokens versus 400K.
Side by side
| GPT-5.1 | Muse Spark 1.3 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 49.0 | 54.8 |
| Released | 2025-11-13 | 2026-09-02 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 1.05M |
| Max output | 128K | 131K |
| Input $ / M tokens | $1.25 | $1.25 |
| Output $ / M tokens | $10 | $4.25 |
| Results tracked | 63 | 37 |
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Category by category
Coding Muse Spark 1.3 leads
GPT-5.1: 46.4 (#66), Muse Spark 1.3: 56.6 (#21)
| Benchmark | GPT-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena WebDev | 1395 | 1657 |
| SciCode | 43.3% | 59.7% |
| LMArena Coding | 1454 | 1514 |
| SWE-bench Verified | 68% | — |
| SWE-bench Verified (bash only) | 66% | — |
| CursorBench | — | 41.6% |
| GSO | 13.7% | — |
| WeirdML | 60.8% | — |
| LiveBench Coding | 72.5% | — |
| ALE-Bench | 1,192 | — |
Agentic & Tool Use Muse Spark 1.3 leads
GPT-5.1: 32.7 (#60), Muse Spark 1.3: 38.6 (#30)
| Benchmark | GPT-5.1 | Muse Spark 1.3 |
|---|---|---|
| Terminal-Bench | 47.6% | — |
| APEX-Agents | — | 57.8% |
| DeepResearch Bench | 42.8% | — |
| GDP.pdf | — | 27.6% |
| LMArena Search | 1199 | — |
| Vending-Bench 2 | 1,473 | — |
Reasoning Muse Spark 1.3 leads
GPT-5.1: 39.8 (#58), Muse Spark 1.3: 54.0 (#27)
| Benchmark | GPT-5.1 | Muse Spark 1.3 |
|---|---|---|
| CritPt | 4.9% | 26% |
| Chess Puzzles | 32% | 38% |
| LMArena Hard Prompts | 1457 | 1503 |
| Mystery Game Puzzles | 19% | 25% |
| DTBench | 90.1% | 96.5% |
| LMCA | 43.9% | 53.9% |
| Epoch Capabilities Index | 149.64 | 156.75 |
| ARC-AGI-2 | 17.6% | — |
| SimpleBench | 53.2% | — |
| NYT Connections (extended) | — | 85.1% |
| ARC-AGI-1 | 72.8% | — |
| EnigmaEval | 11.2% | — |
| LiveBench Reasoning | 95.8% | — |
| LiveBench Data Analysis | 72.1% | — |
| Bench to the Future 3 | — | 0.14 |
| ForecastBench | 58.1 | — |
| LiveBench | 78.8% | — |
Math Muse Spark 1.3 leads
GPT-5.1: 52.2 (#51), Muse Spark 1.3: 73.1 (#21)
| Benchmark | GPT-5.1 | Muse Spark 1.3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.6% | 99.2% |
| LMArena Math | 1447 | 1494 |
| FrontierMath (Tiers 1-3) | — | 74.4% |
| FrontierMath Tier 4 | — | 46.3% |
| ProofBench | — | 58% |
| Omni-MATH | 46.4% | — |
| LiveBench Math | 94.5% | — |
| FrontierMath (Feb 2025 set) | 31% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge GPT-5.1 leads
GPT-5.1: 50.6 (#71), Muse Spark 1.3: 42.6 (#95)
| Benchmark | GPT-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena Expert | 1470 | 1516 |
| GPQA Diamond | 87.6% | — |
| Humanity's Last Exam | 23.7% | — |
| SimpleQA Verified | 48% | — |
| MMLU-Pro | 57.9% | — |
| Vectara Hallucination Rate | 10.9% | — |
| GPQA (HELM) | 44.2% | — |
Multimodal GPT-5.1 leads
GPT-5.1: 44.8 (#19), Muse Spark 1.3: 43.7 (#22)
| Benchmark | GPT-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | 1250 | 1309 |
| LMArena Document | 1403 | 1471 |
| VPCT | 58.7% | — |
Multilingual Muse Spark 1.3 leads
GPT-5.1: 53.8 (#56), Muse Spark 1.3: 57.4 (#8)
| Benchmark | GPT-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1431 | 1481 |
| LMArena Chinese | 1495 | 1529 |
| LMArena French | 1450 | 1524 |
| LMArena German | 1438 | 1515 |
| LMArena Japanese | 1453 | 1474 |
| LMArena Korean | 1401 | 1501 |
| LMArena Russian | 1435 | 1490 |
| LMArena Spanish | 1433 | 1490 |
Instruction Following GPT-5.1 leads
GPT-5.1: 83.9 (#1), Muse Spark 1.3: 77.5 (#22)
| Benchmark | GPT-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1443 | 1477 |
| LiveBench Instruction Following | 93.3% | — |
| IFEval | 93.5% | — |
Long Context GPT-5.1 leads
GPT-5.1: 47.6 (#14), Muse Spark 1.3: 45.6 (#32)
| Benchmark | GPT-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1447 | 1488 |
| CL-bench | 23.7% | — |
| CL-bench Life | 17.3% | — |
Writing & Preference Muse Spark 1.3 leads
GPT-5.1: 64.5 (#55), Muse Spark 1.3: 73.6 (#9)
| Benchmark | GPT-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1443 | 1490 |
| LMArena Creative Writing | 1427 | 1455 |
| LMArena Multi-Turn | 1450 | 1482 |
| EQ-Bench Creative Writing | — | 1906 |
| WildBench | 86.3% | — |
| LiveBench Language | 80.2% | — |
Frequently asked questions
Is GPT-5.1 better than Muse Spark 1.3?
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 49.0 on the Noometry Index.
Which is cheaper, GPT-5.1 or Muse Spark 1.3?
Muse Spark 1.3 is cheaper. It lists at $1.25 per million input tokens and $4.25 per million output tokens; GPT-5.1 lists at $1.25 and $10.
Is GPT-5.1 or Muse Spark 1.3 better for coding?
Muse Spark 1.3 scores higher on coding benchmarks: 56.6 versus 46.4 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.3 does, with 1.05M tokens against 400K.
How many benchmarks do GPT-5.1 and Muse Spark 1.3 share?
28 benchmarks have published results for both models. GPT-5.1 has 63 scored results on Noometry and Muse Spark 1.3 has 37.